Increased Risk of Systemic Lupus Erythematosus in 29,000 Patients with Biopsy-verified Celiac Disease
Bibliographic record
Abstract
OBJECTIVE: To investigate a possible association between celiac disease (CD) and systemic lupus erythematosus (SLE). Case series have indicated a possible association, but population-based studies are lacking. METHODS: We compared the risk of SLE in 29,048 individuals with biopsy-verified CD (villous atrophy, Marsh 3) from Sweden's 28 pathology departments with that in 144,352 matched individuals from the general population identified through the Swedish Total Population Register. SLE was defined as having at least 2 records of SLE in the Swedish Patient Register. We used Cox regression to estimate hazard ratios (HR) for SLE. RESULTS: During followup, 54 individuals with CD had an incident SLE. This corresponded to an HR of 3.49 (95% CI 2.48-4.90), with an absolute risk of 17/100,000 person-years and an excess risk of 12/100,000. Beyond 5 years of followup, the HR for SLE was 2.54 (95% CI 1.57-4.10). While SLE was predominantly female, we found similar risk estimates in men and women. When we restricted our outcome to individuals who also had a dispensation for a medication used in SLE, the HR was 2.43 (95% CI 1.22-4.87). The HR for having 2 records of SLE diagnoses, out of which at least 1 had occurred in a department of rheumatology, nephrology/dialysis, internal medicine, or pediatrics, was 2.87 (95% CI 1.97-4.17). CONCLUSION: Individuals with CD were at a 3-fold increased risk of SLE compared to the general population. Although this excess risk remained more than 5 years after CD diagnosis, absolute risks were low.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".